Application of multi-objective optimization in the study of anti-breast cancer candidate drugs.

ABSTRACT: In the development of anti-breast cancer drugs, the quantitative structure-activity relationship model of compounds is usually used to select potential active compounds. However, the existing methods often have problems such as low model prediction performance, lack of overall consideration of the biological activity and related properties of compounds, and difficulty in directly selection candidate drugs. Therefore, this paper constructs a complete set of compound selection framework from three aspects: feature selection, relationship mapping and multi-objective optimization problem solving. In feature selection part, a feature selection method based on unsupervised spectral clustering is proposed. The selected features have more comprehensive information expression ability. In the relati

SUBMITTER: Mei Y 

PROVIDER: S-EPMC9652409 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature